Optical flow estimator.
It is well-known that PWC-Net [1]} is one of the state-of-the-art optical flow methods. However, as a sub-module in the model of point cloud frame interpolation, its computational complexity is not desirable. Therefore, we modify PWC-Lite [2]}, a lightweight architecture of PWC-Net, as our flow estimator. Our method follows the main pipeline of PWC-Lite, but with some adaptions in two aspects. (1) The original implementation aims to predict bi-directional optical flows for multiple frames. For low complexity and consistency with the input frame numbers of our system, we reduce the model size to estimate the optical flow only for two frames. The structure is depicted in Fig. REF  (top). (2) The loss function adopted in original PWC-Lite, is a measurement of pixel-wise similarities between color images. However, as mentioned previously, the inherited characteristics of range images are drastically different from that of color images. Therefore, Charbonnier penalty function [3]} is utilized as the loss function due to its smoothness and robustness.
